Linear Regression vs Logistic Regression | Edureka

Linear Regression vs Logistic Regression | Edureka

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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Agenda 32 41 5 Types of Machine Learning Regression Vs Classification What is Linear Regression? Linear Regression Use case What is Logistic Regression? 6 Logistic Regression Use case 7 Linear Vs Logistic Regression
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Types Of Machine Learning
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Types Of Machine Learning Reinforcement LearningSupervised Learning Unsupervised Learning
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Regression And Classification Machine Learning Supervised learning Unsupervised learning Reinforcement learning Classification Regression
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Regression Vs Classification
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Regression Vs Classification Classification Regression Classification is the task of predicting a discrete class label Regression is the task of predicting a continuous quantity • In a classification problem data is classified into one of two or more classes • A classification problem with two classes is called binary, more than two classes is called a multi-class classification Spam Non-Spam Mail • A regression problem requires the prediction of a quantity • A regression problem with multiple input variables is called a multivariate regression problem Predicted price Actual price Time Price
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Linear Regression?
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Linear Regression? Linear Regression is a method to predict dependent variable (Y) based on values of independent variables (X). It can be used for the cases where we want to predict some continuous quantity. • Dependent variable (Y): The response variable who’s value needs to be predicted. • Independent variable (X): The predictor variable used to predict the response variable. The following equation is used to represent a linear regression model: Y= 𝒃 𝟎 + 𝒃 𝟏 𝒙 + ⅇx y independent variable dependentvariable
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Linear Regression? Linear Regression is a method to predict dependent variable (Y) based on values of independent variables (X). It can be used for the cases where we want to predict some continuous quantity. x y independent variable dependentvariable Y= 𝒃 𝟎 + 𝒃 𝟏 𝒙 + ⅇ dependent variable Y intercept Slope independent variable Error Y intercept ( 𝑏0) Error (e) Slope ( 𝑏1)
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Logistic Regression?
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Logistic Regression? Logistic Regression is a method used to predict a dependent variable, given a set of independent variables, such that the dependent variable is categorical. x y independent variable dependentvariable 0 1 • Dependent variable (Y): The response binary variable holding values like 0 or 1, Yes or No, A, B or C • Independent variable (X): The predictor variable used to predict the response variable. The following equation is used to represent a linear regression model: 𝐘 𝟏 − 𝐘 log = C + B1X1 + B2X2 + ….
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science What Is Logistic Regression? Logistic Regression is a method used to predict a dependent variable, given a set of independent variables, such that the dependent variable is categorical. x y independent variable dependentvariable 0 1 𝐘 𝟏 − 𝐘 log = C + B1X1 + B2X2 + …. • Y is the probability of an event to happen which you are trying to predict • x1, x2 are the independent variables which determine the occurrence of an event i.e. Y • C is the constant term which will be the probability of the event happening when no other factors are considered
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Linear Regression Use Case
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Linear Regression Use Case To forecast monthly sales by studying the relationship between the monthly e-commerce sales and the online advertising costs. Monthly sales Advertising cost In 1000s 200 900 450 680 490 300 0.5 5 1.9 3.2 2.0 1.0 200 400 600 800 1000 1.0 2.0 3.0 4.0 5.0 Cost in 1000s Monthlysales y x
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Logistic Regression Use Case
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Logistic Regression Use Case To predict if a student will get admitted to a school based on his CGPA. Admission CGPA 0 0 0 1 1 1 4.2 5.1 5.5 8.2 9.0 9.1 0 1 2.0 4.0 6.0 8.0 10 CGPA Admission y x
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Linear Regression Vs Logistic Regression
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science Linear Regression Vs Logistic Regression
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science YouTube Video Link in the Description
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  DATA SCIENCE CERTIFICATIONTRAINING www.edureka.co/data-science WebDriver vs. IDE vs. RC ➢ Data Warehouse is like a relational database designed for analytical needs. ➢ It functions on the basis of OLAP (Online Analytical Processing). ➢ It is a central location where consolidated data from multiple locations (databases) are stored.